Clustering Plasmodium falciparum Genes to their Functional Roles Using k-means

We developed recently a new and novel Metric Matrics k-means (MMk-means) clustering algorithm to cluster genes to their functional roles with a view of obtaining further knowledge on many P. falciparum genes. To further pursue this aim, in this study, we compare three different k-means algorithms (including MMk-means) results from an in-vitro microarray data (Le Roch et al., Science, 2003) with the classification from an in-vivo microarray data (Daily et al., Nature, 2007) in other to perform a comparative functional classification of P. falciparum genes and further validate the effectiveness of our MMk-means algorithm. Results from this study indicate that the resulting distribution of the comparison of the three algorithms’ in vitro clusters against the in vivo clusters are similar thereby authenticating our MMk-means method and its effectiveness. However, Daily et al. claim that the physiological state (the environmental stress response) of P. falciparum in selected malaria-infected patients observed in one of their clusters can not be found in any in-vitro clusters is not true as our analysis reveal many in-vitro clusters representation in this cluster

Reducing the Time Requirement of k-Means Algorithm

Traditional k-means and most k-means variants are still computationally expensive for large datasets, such as microarray data, which have large datasets with large dimension size d. In k-means clustering, we are given a set of n data points in ddimensional space Rd and an integer k. The problem is to determine a set of k points in Rd, called centers, so as to minimize the mean squared distance from each data point to its nearest center. In this work, we develop a novel k-means algorithm, which is simple but more efficient than the traditional k-means and the recent enhanced k-means. Our new algorithm is based on the recently established relationship between principal component analysis and the k-means clustering. We provided the correctness proof for this algorithm. Results obtained from testing the algorithm on three biological data and six non-biological data (three of these data are real, while the other three are simulated) also indicate that our algorithm is empirically faster than other known k-means algorithms. We assessed the quality of our algorithm clusters against the clusters of a known structure using the Hubert-Arabie Adjusted Rand index (ARIHA). We found that when k is close to d, the quality is good (ARIHA.0.8) and when k is not close to d, the quality of our new k-means algorithm is excellent (ARIHA.0.9). In this paper, emphases are on the reduction of the time requirement of the k-means algorithm and its application to microarray data due to the desire to create a tool for clustering and malaria research. However, the new clustering algorithm can be used for other clustering needs as long as an appropriate measure of distance between the centroids and the members is used. This has been demonstrated in this work on six non-biological data

Costing the supply chain for delivery of ACT and RDTs in the public sector in Benin and Kenya

Studies have shown that supply chain costs are a significant proportion of total programme costs. Nevertheless, the costs of delivering specific products are poorly understood and ballpark estimates are often used to inadequately plan for the budgetary implications of supply chain expenses. The purpose of this research was to estimate the country level costs of the public sector supply chain for artemisinin-based combination therapy (ACT) and rapid diagnostic tests (RDTs) from the central to the peripheral levels in Benin and Kenya.MethodsA micro-costing approach was used and primary data on the various cost components of the supply chain was collected at the central, intermediate, and facility levels between September and November 2013. Information sources included central warehouse databases, health facility records, transport schedules, and expenditure reports. Data from document reviews and semi-structured interviews were used to identify cost inputs and estimate actual costs. Sampling was purposive to isolate key variables of interest. Survey guides were developed and administered electronically. Data were extracted into Microsoft Excel®, and the supply chain cost per unit of ACT and RDT distributed by function and level of system was calculated.ResultsIn Benin, supply chain costs added USD 0.2011 to the initial acquisition cost of ACT and USD 0.3375 to RDTs (normalized to USD 1). In Kenya, they added USD 0.2443 to the acquisition cost of ACT and USD 0.1895 to RDTs (normalized to USD 1). Total supply chain costs accounted for more than 30% of the initial acquisition cost of the products in some cases and these costs were highly sensitive to product volumes. The major cost drivers were found to be labour, transport, and utilities with health facilities carrying the majority of the cost per unit of product. Accurate cost estimates are needed to ensure adequate resources are available for supply chain activities. Product volumes should be considered when costing supply chain functions rather than dollar value. Further work is needed to develop extrapolative costing models that can be applied at country level without extensive micro-costing exercises. This will allow other countries to generate more accurate estimates in the future

Trends in malaria morbidity among health care-seeking children under age five in Mopti and Sevare, Mali between 1998 and 2006

Abstract Background In Mali, malaria is the leading cause of death and the primary cause of outpatient visits for children under five. The twin towns of Mopti and Sévaré have historically had high under-five mortality. This paper investigates the changing malaria burden in children under five in these two towns for the years 1998-2006, and the likely contribution of previous interventions aimed at reducing malaria. Methods A retrospective analysis of daily outpatient consultation records from urban community health centres (CSCOMs) located in Mopti and Sévaré for the years 1998-2006 was conducted. Risk factors for a diagnosis of presumptive malaria, using logistic regression and trends in presumptive malaria diagnostic rates, were assessed using multilevel analysis. Results Between 1998-2006, presumptive malaria accounted for 33.8% of all recorded consultation diagnoses (10,123 out of 29,915). The monthly presumptive malaria diagnostic rate for children under five decreased by 66% (average of 8 diagnoses per month per 1,000 children in 1998 to 2.7 diagnoses per month in 2006). The multi-level analysis related 37% of this decrease to the distribution of bed net treatment kits initiated in May of 2001. Children of the Fulani (Peuhl) ethnicity had significantly lower odds of a presumptive malaria diagnosis when compared to children of other ethnic groups. Conclusions Presumptive malaria diagnostic rates have decreased between 1998-2006 among health care-seeking children under five in Mopti and Sévaré. A bed net treatment kit intervention conducted in 2001 is likely to have contributed to this decline. The results corroborate previous findings that suggest that the Fulani ethnicity is protective against malaria. The findings are useful to encourage dialogue around the urban malaria situation in Mali, particularly in the context of achieving the target of reducing malaria morbidity in children younger than five by 50% by 2011 as compared to levels in 2000.</p

Cost-effectiveness of community-based screening and treatment of moderate acute malnutrition in Mali.

IntroductionModerate acute malnutrition (MAM) causes substantial child morbidity and mortality, accounting for 4.4% of deaths and 6.0% of disability-adjusted life years (DALY) lost among children under 5 each year. There is growing consensus on the need to provide appropriate treatment of MAM, both to reduce associated morbidity and mortality and to halt its progression to severe acute malnutrition. We estimated health outcomes, costs and cost-effectiveness of four dietary supplements for MAM treatment in children 6-35 months of age in Mali.MethodsWe conducted a cluster-randomised MAM treatment trial to describe nutritional outcomes of four dietary supplements for the management of MAM: ready-to-use supplementary foods (RUSF; PlumpySup); a specially formulated corn-soy blend (CSB) containing dehulled soybean flour, maize flour, dried skimmed milk, soy oil and a micronutrient pre-mix (CSB++; Super Cereal Plus); Misola, a locally produced, micronutrient-fortified, cereal-legume blend (MI); and locally milled flour (LMF), a mixture of millet, beans, oil and sugar, with a separate micronutrient powder. We used a decision tree model to estimate long-term outcomes and calculated incremental cost-effectiveness ratios (ICERs) comparing the health and economic outcomes of each strategy.ResultsCompared to no MAM treatment, MAM treatment with RUSF, CSB++, MI and LMF reduced the risk of death by 15.4%, 12.7%, 11.9% and 10.3%, respectively. The ICER was US$9821 per death averted (2015 USD) and US$347 per DALY averted for RUSF compared with no MAM treatment.ConclusionMAM treatment with RUSF is cost-effective across a wide range of willingness-to-pay thresholds.Trial registrationNCT01015950

Percent Fat Mass Increases with Recovery, But Does Not Vary According to Dietary Therapy in Young Malian Children Treated for Moderate Acute Malnutrition.

BackgroundModerate acute malnutrition (MAM) affects 34.1 million children globally. Treatment effectiveness is generally determined by the amount and rate of weight gain. Body composition (BC) assessment provides more detailed information on nutritional stores and the type of tissue accrual than traditional weight measurements alone.ObjectiveThe aim of this study was to compare the change in percentage fat mass (%FM) and other BC parameters among young Malian children with MAM according to receipt of 1 of 4 dietary supplements, and recovery status at the end of the 12-wk intervention period.MethodsBC was assessed using the deuterium oxide dilution method in a subgroup of 286 children aged 6-35 mo who participated in a 12-wk community-based, cluster-randomized effectiveness trial of 4 dietary supplements for the treatment of MAM: 1) lipid-based, ready-to-use supplementary food (RUSF); 2) special corn-soy blend "plus plus" (CSB++); 3) locally processed, fortified flour (MI); or 4) locally milled flours plus oil, sugar, and micronutrient powder (LMF). Multivariate linear regression modeling was used to evaluate change in BC parameters by treatment group and recovery status.ResultsMean&nbsp;±&nbsp;SD %FM at baseline was 28.6%&nbsp;±&nbsp;5.32%. Change in %FM did not vary between groups. Children who received RUSF vs. MI gained more (mean; 95% CI) weight (1.43; 1.13, 1.74 kg compared with 0.84; 0.66, 1.03 kg; P&nbsp;=&nbsp;0.02), FM (0.70; 0.45, 0.96 kg compared with 0.20; 0.05, 0.36 kg; P&nbsp;=&nbsp;0.01), and weight-for-length z score (1.23; 0.79, 1.54 compared with 0.49; 0.34, 0.71; P&nbsp;=&nbsp;0.03). Children who recovered from MAM exhibited greater increases in all BC parameters, including %FM, than children who did not recover.ConclusionsIn this study population, children had higher than expected %FM at baseline. There were no differences in %FM change between groups. International BC reference data are needed to assess the utility of BC assessment in community-based management of acute malnutrition programs. This trial was registered at clinicaltrials.gov as NCT01015950

Surpoids et obésité dans la population générale de 5 à 19 ans en milieu urbain bamakois (Mali)

Introduction:&nbsp;déterminer la prévalence du surpoids et de l'obésité dans la population âgée de 5 à 19 ans et fournir des données de référence pour de futures études. Méthodes:&nbsp;notre échantillon est issu de la première étude sur les pathologies cardiovasculaires basée sur l'approche STEP de l'Organisation Mondiale de la Santé (OMS) en sélectionnant tous les sujets âgés de 5 à 19 ans. Nous avons utilisé les méthodes de l'OMS et de l'International Obesity Task Force (IOTF) pour déterminer la prévalence du surpoids et de l'obésité dans la population générale. Résultats:&nbsp;la moyenne d'âge était de 11,75 ans ± 4,387 et le sex-ratio M:F était de 0,79. les moyennes pour le poids et la taille étaient de 36,85 kg et 143,48 cm. Selon les critères OMS 1,61% des garçons et 3,28 % des filles étaient en surpoids et 0,92% des garçons contre 1,46% des filles obèses. Selon les critères de l'IOTF 4,10% des garçons et 5,94% des filles étaient en surpoids tandis que 0,72% des garçons et 2,68% des filles étaient obèses. Conclusion:&nbsp;malgré sa faible prévalence le surpoids et l'obésité doivent être régulièrement étudiés pour reconnaître des tendances et prendre des mesures adéquates de prévention. Les 2 méthodes utilisées ont permis d'avoir des données de référence pour de futures études au Mali et ailleurs

Surpoids et obésité dans la population au-dessus de 20 ans en milieu urbain bamakois (Mali)

Introduction:&nbsp;il est question dans notre travail d'étudier le SP et l'OB et les facteurs associés dans la population âgée de 20 ans ou plus. Méthodes:&nbsp;notre échantillon a été obtenu à partir d'une enquête sur les pathologies cardiovasculaires dans le District de Bamako et impliquant 2199 sujets de 5-104 ans, en sélectionnant tous les sujets âgés d'au moins 20 ans (1162). Pour chaque sujet, l'IMC, rapport taille / hanche et le tour de taille ont été déterminées. Les données ont été analysées avec SPSS 12. Résultats:&nbsp;l'âge moyen était de 36,86 années, 61,4% étaient des femmes, 49,7% dans le secteur informel et 38,0% avaient réalisé l'enseignement primaire. Facteurs de risque cardiovasculaires étaient l'inactivité physique (72,4%), le tabagisme (12,2%) et hypertension (26,7%). La prévalence de l'obésité était de 8,8 et 14,7% respectivement sur la base de l'indice de masse et le tour de taille. Conclusion:&nbsp;le SP et l'OB sont à prendre en compte dans les mesures de politique sanitaire que dans la pratique quotidienne des professionnels de santé, il est peut-être plus utile d'utiliser plusieurs paramètres pour être à même de bien stratifier nos patients par rapport à leur risque

Reducing the Time Requirement of k-Means Algorithm

Traditional k-means and most k-means variants are still computationally expensive for large datasets, such as microarray data, which have large datasets with large dimension size d. In k-means clustering, we are given a set of n data points in ddimensional space Rd and an integer k. The problem is to determine a set of k points in Rd, called centers, so as to minimize the mean squared distance from each data point to its nearest center. In this work, we develop a novel k-means algorithm, which is simple but more efficient than the traditional k-means and the recent enhanced k-means. Our new algorithm is based on the recently established relationship between principal component analysis and the k-means clustering. We provided the correctness proof for this algorithm. Results obtained from testing the algorithm on three biological data and six non-biological data (three of these data are real, while the other three are simulated) also indicate that our algorithm is empirically faster than other known k-means algorithms. We assessed the quality of our algorithm clusters against the clusters of a known structure using the Hubert-Arabie Adjusted Rand index (ARIHA). We found that when k is close to d, the quality is good (ARIHA.0.8) and when k is not close to d, the quality of our new k-means algorithm is excellent (ARIHA.0.9). In this paper, emphases are on the reduction of the time requirement of the k-means algorithm and its application to microarray data due to the desire to create a tool for clustering and malaria research. However, the new clustering algorithm can be used for other clustering needs as long as an appropriate measure of distance between the centroids and the members is used. This has been demonstrated in this work on six non-biological data